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Water resources management, forecasting, and decision making require reliable estimates of precipitation. Extreme precipitation events are of particular importance because of their severe impact on the economy, the environment, and the society. In recent years, the emergence of various satellite-retrieved precipitation products with high spatial resolutions and global coverage have resulted in new sources of uninterrupted precipitation estimates. However, satellite-based estimates are not well integrated into operational and decision-making applications because of a lack of information regarding the associated uncertainties and reliability of these products. In this study, four satellite-derived precipitation products (CMORPH, PERSIANN, TMPA-RT, and TMPA-V6) are evaluated with respect to their performance in capturing precipitation extremes. The Stage IV (radar-based, gauge-adjusted) precipitation estimates are used as reference data. The results show that with respect to the probability of detecting extremes and the volume of correctly identified precipitation, CMORPH and PERSIANN data sets lead to better estimates. However, their false alarm ratio and volume are higher than those of TMPA-RT and TMPA-V6. Overall, no single precipitation product can be considered ideal for detecting extreme events. In fact, all precipitation products tend to miss a significant volume of rainfall. With respect to verification metrics used in this study, the performance of all satellite products tended to worsen as the choice of extreme precipitation threshold increased. The analyses suggest that extensive efforts are necessary to develop algorithms that can capture extremes more reliably.


This article was originally published in Journal of Geophysical Research-Atmospheres, volume 116, in 2011. DOI: 10.1029/2010JD014741


American Geophysical Union



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